This course has been replaced.

To be effective in a competitive business environment, a business analyst needs to be able to use predictive analytics to translate information into decisions and to convert information about past performance into reliable forecasts. An effective analyst also should be able to identify the analytical tools and data structures to anticipate market trends.

In this course, you gain the skills required to succeed in today's highly analytical and data-driven economy. This course introduces the basics of data management, decision trees, logistic regression, segmentation, design of experiments, and forecasting.

This course combines scheduled, instructor-led Live Web sessions with independent activities, such as reading assignments and hands-on exercises, for a highly engaging learning experience. The course is delivered over a period of five weeks with an online orientation in week one and two or three Live Web sessions per week thereafter. Students communicate with classmates and the instructor during Live Web sessions and through online forums. To achieve maximum benefit from this course, students should allocate 8 to 12 hours per week to the following:

participating in the two or three weekly Live Web sessions with your instructor (3.5 hours each)

completing all weekly assignments (these can include reading assignments and hands-on exercises) before the next scheduled Live Web session (1 to 1.5 hours a week).

Upon request, this course can also be delivered as a private 5-day on-site class at your location or a SAS training center.

Learn how to

express a business problem as a manageable analytical question

identify the appropriate data to address the question

select statistical analyses that help answer the question

select a champion from a set of competing models (analyses)

apply the results of the champion analysis to new data for scoring, forecasting, or both